Modern wireless communication networks include many different network topologies comprising heterogeneous mixtures of macrocell, microcell, picocell, and femtocell resources. At the highest level of wireless coverage, a macrocell provides cellular service for a relatively large physical area, often in areas where network traffic densities are low. In more dense traffic areas, a macrocell may act as an overarching service provider, primarily responsible for providing continuity for service area gaps between smaller network cells. In areas of increased traffic density, microcells are often utilized to add network capacity and to improve signal quality for smaller physical areas where increased bandwidth is required. Numerous picocells and femtocells generally add to network capacity for even smaller physical areas in highly populated metropolitan and residential regions of a larger data communications network.
As would be understood by those skilled in the Art, in all wireless service provider networks, macrocells typically provide the largest wireless coverage area for licensed frequency spectra, followed by microcells, then picocells, and lastly femtocells. By way of example, in a typical wireless data communications network, a macrocell base station may provide a wireless coverage area ranging between one to five kilometers, radially from the center of the cell; a microcell base station may provide a coverage area ranging between one-half to one kilometer radially; a picocell base station may provide a coverage area ranging between 100 to 500 meters radially; and a femtocell base station may provide a coverage area of less than 100 meters radially. Each of these network cells or base station types are generally configured to connect with a particular service provider network using various common wireline communications technologies, including, but not limited to: fiber optic, twisted pair, powerline, and/or coaxial cable (i.e., joining cells to a backhaul network).
This mixture of larger and smaller cells can reduce periods of network congestion created by traditional network architecture which previously bottlenecked a majority of regional subscriber communications through a small number of larger network cells (e.g., macrocells or microcells). This congestion reducing technique can improve a service provider network's Quality of Service (QOS) as well as network service subscribers' collective Quality of Experience (QOE) within a particular portion of a data communications network. Negative effects associated with poor QOS and poor QOE (e.g., conditions largely caused by congestion and/or interference), which can be mitigated by adding a substantial number of short-range wireless transceiver devices to network infrastructure, may include: queuing delay, data loss, as well as blocking of new and existing network connections for certain network subscribers.
As the number of overlapping cells in a network increases (i.e., the number of macrocells, microcells, picocells, and femtocells in a network), it becomes increasingly important to manage the airlink resources shared by the components in a network. By way of example, resources such as frequency channels, timeslots, and spreading codes need to be managed for each cell in a network, and often it is advantageous to manage voice traffic and data traffic separately to increase overall network efficiency.
Managing voice traffic presents two difficulties when compared to managing data traffic. First, voice traffic is less robust than data traffic, and second, errors affecting voice traffic are often more noticeable than errors affecting data traffic. More specifically, subscribers expect a high QOS and QOE with voice communications, although this is often difficult to deliver because voice traffic is sensitive to delay and packet errors. Because voice traffic is a streaming traffic type, one method of controlling interference levels may be to use a closed-loop power control system. One type of closed-loop algorithm may constantly monitor an uplink transmission from a subscriber device and vary the power level of a downlink channel to an optimum power level. This may allow voice traffic to be transmitted at a lower power level, thereby reducing interference with other resources in adjacent cells within the system. However, as the nature of the traffic transitions from streaming to burst transmissions, the closed-loop power control algorithm becomes less effective and interference levels may increase.
In contrast to voice traffic, data traffic is bursty in nature and closed-loop power control algorithms cannot typically be used to control power levels while transmitting data traffic, leading to greater levels of interference in neighboring cells. Additionally, data traffic is less sensitive than voice traffic to delay and can tolerate packet errors since retransmission is used to correct for lost packets. Given the more robust nature of data traffic and the less effective response to some power control algorithms, it would be advantageous to manage data traffic differently than voice traffic to reduce interference levels and to increase system efficiency.
Without effective wireless resource management, data traffic in one cell could create interference issues with voice traffic in an adjacent cell because voice traffic is more susceptible than data traffic to errors in a wireless network. Thus, it is desirable if the resources used for these types of traffic in a network of cells could be coordinated in resource zones such that all cells used similar sets of resources for each type of traffic.
Prior art systems have attempted to manage network traffic through network planning and by pre-provisioning sets of resources for each cell in a network. These centrally-planned networks have managed frequency channels, timeslots, and spreading codes, but efficiency suffers as the provisioning may be conservative and may not react effectively to actual traffic requirements. Alternatively, prior art systems using packetized voice traffic and data traffic have managed resources in an ad hoc manner without differentiating between the traffic types leading to the aforementioned interference issues. Thus, it would be desirable for cells to negotiate between themselves for the resources they need from within sets of resources that have significant, if not complete, overlap between cells thereby, controlling interference levels and resulting in a more efficient resource utilization than a planned and managed scheme would yield.